The world is full of sensor devices for detecting physical phenomena and for providing a signal in response to the phenomena. For example, a thermometer converts the physical condition temperature into a visual signal, a height of mercury in a glass column. Another example of a temperature-sensing device is a thermocouple which converts the physical condition temperature into an electrical signal. To be useful the sensor signal has to be understood to correspond with a particular physical phenomenon. For example, the thermometer has lines on the glass column to indicate the degrees of temperature. The lines, of course, have to be in the right locations on the glass column to have meaning, and the process by which the lines are properly located is known as calibration. During calibration the sensor is subjected to a known physical condition or conditions and its response is observed. Observing the response of the sensor to the known conditions allows one to predict the sensor response for a wide range of conditions.
Pressure sensors are devices that provide a signal indicative of pressure, for example, the amount of air pressure within a tire. As with other types of sensors, pressure sensors require calibration to be useful. A specific kind of pressure sensor known as a piezoresistive pressure sensor provides a voltage signal indicative of pressure. The piezoresistive pressure sensor poses a number of problems in application. For example, the piezoresistive sensing element provides a relatively low level voltage signal. In addition, the piezoresistive sensing element may provide a signal that is sensitive to changing temperature and that does not change linearly with changing pressure. Moreover, the signal voltage characteristic from one sensing element to another sensing element may not be consistent. Therefore, special signal conditioning circuitry is required for a sensor product that provides a high level sensor output that is sufficiently accurate across a wide range of operating temperatures and pressures. Importantly, the device has to be capable of mass production, at low cost and with a high degree of part-to-part repeatability.
Most low cost signal conditioning approaches use analog circuits that are adjusted during a calibration process. For example, it is known to use amplifier circuits coupled to resistor networks. In one such application, the resistor network includes a number of resistive elements coupled by fusible links. Though limited in the degree of adjustment available, various resistive values may be established for providing an acceptable output from the amplifier network. In another application, the resistor network includes laser trimmable resistive elements. During a calibration process, the resistive elements are trimmed using a laser to achieve the correct resistive values to provide an acceptable output from the amplifier network. In either application access to the circuit may be required during processing in order to fuse links and/or laser trim components. Hence manufacturing processing options are limited. Also, in certain applications offset, sensitivity and linearity may be difficult to compensate for independently. Furthermore, processing activities following calibration may introduce error that can not be corrected in the final product. And, the laser trim process requires expensive processing hardware and suffers increased cycle time.
An alternative design provides for electronic calibration of the sensing element. Sensors adapted for electronic calibration have included a microprocessor coupled to the sensor element via suitable signal conditioning circuitry and to a memory in which a calibration method is retained. During processing, the sensing element is tested under various known-operating conditions. Calibration values are established and stored in the memory. In operation, the microprocessor in conjunction with the method and calibration values operates to provide a sensor output. Other implementations use digital signal processors (DSPs) to perform the required calculations on digitized values of the sensor element output.
Systems implemented using digital technology generally consist of 1) front-end analog signal conditioning, 2) analog-to-digital conversion, 3) digital processing, 4) digital-to-analog conversion and 5) back-end analog signal output drive. The front-end conditioning often consists of digitally programmable gain and offset functions, in which the offset signal is usually generated by some form of digital-to-analog converter (DAC). If the signal conditioning circuit also includes some form of disturbance variable compensation, the disturbance variable signal is also front-end conditioned and digitized.
It is possible, then, that the sensor signal conditioning circuit may require at least two analog-to-digital converters (ADCs). One to digitize the sensing element output and one to digitize the disturbance variable signal. Front-end signal conditioning of the sensing element output and disturbance variable may require DAC devices to provide the appropriate control signal to the conditioning circuits. Also, the digitized corrected sensor output requires conversion back to analog. Thus, the signal conditioning circuit may require two ADCs and as many as three DACs. These devices are die area intensive in integrated circuit implementations, particularly in that the accuracy of ADCs and DACs is directly related to the physical size of the matching components (capacitors, resistors, transistors, etc.) used to make up the devices. The substantial amount of die area required to implement the several analog-to-digital and digital-to-analog operations has hampered the use of digital technology in sensor signal conditioning applications.
The typical successive approximation implementation of an ADC includes at least one DAC. It has been recognized in the art that where both analog-to-digital and digital-to-analog conversion (A/D and D/A, respectively) are required it may be possible to reuse the DAC in the ADC device. Examples of this architecture fail to address circuit implementations requiring numerous A/D and D/A conversion operations such as required in the sensors signal conditioning circuit, which includes several D/A outputs and several A/D inputs.
Therefore, there remains a need for an electronically calibrated sensing device using digital signal processing that makes efficient use of ADC and DAC devices so as to minimize the number of such devices in the signal conditioning circuit. The sensing device preferably includes a signal processing circuit that provides for digital calibration of the sensor and its analog input conditioning circuits. Essentially, a more silicon efficient and accurate approach is needed.